Integrated optimisation of loading schedules and delivery routes

ABSTRACT

In warehouses, routing decisions for vehicles are highly related to the schedule of docks and loading operations. To mind the gap that most existing studies consider the routing decisions solely, this study investigates the vehicle routing problem with time windows and loading scheduling (VRPTW-LS). In this problem, the loading schedules at the loading docks and the visiting sequences for vehicles are determined to minimise the total travelled distance. To solve this problem, an adaptive large neighbourhood search algorithm, embedded with a tailored solution representation and an efficient feasibility check mechanism, is developed. In addition, the results of extensive computational experiments verify the effectiveness and efficiency of the proposed algorithm, and some analyses are conducted to obtain managerial insights.

KEYWORDS:

• Logistics
• routing
• loading docks
• loading scheduling
• adaptive large neighbourhood search

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author, Xin Wang ([email protected]), upon reasonable request.

Additional information

Funding

This work is supported by the grant from the Young Elite Scientists Sponsorship Program by China Association for Science and Technology [grant number 2019QNRC001] and the National Natural Science Foundation of China under [grant number 71732003].

Notes on contributors

Yijing Liang

Yijing Liang received her B.E. degree from the School of Traffic & Transportation Engineering, Central South University, China, in 2016 and her Ph.D. degree in the School of Management and Engineering from Nanjing University, China, in 2021. She is a lecturer in the School of Traffic and Transport Engineering, Changsha University of Science and Technology. Her research interests include vehicle routing, combinatorial optimisation and logistics system optimisation.

Xin Wang

Xin Wang is a Ph.D. student in the Department of Industrial Systems Engineering and Management of the National University of Singapore. He received his B.S., M.S. degrees from Central South University, China, in 2016 and 2019, respectively. His research interests include vehicle routing and optimisation in maritime operations.

Zhixing Luo

Zhixing Luo is an Associate Professor of Industrial Engineering in the School of Management and Engineering at Nanjing University. He received his B.Sc. degree in Computer Science from the South China University of Technology, and his Ph.D. degree in Management Sciences from the City University of Hong Kong. His research interests include vehicle routing, combinatorial optimisation, network design and exact algorithms.

Dezhi Zhang

Dezhi Zhang received the B.S., M.S. degree and Ph.D. degrees from Central South University, China, in 1999, 2002 and 2006, respectively. He is currently a Professor in the School of Traffic & Transportation Engineering, Central South University. His research interests are green logistic network design and optimisation, green vehicle routing problem and schedule, optimisation of green supply chain network design, and optimisation of multimodal freight transport based on low-carbon.